Entity resolution can generally be defined as a process of determining whether two expressions (or “mentions”) in natural language text refer to the same entity. Given a collection of mentions of entities extracted from a body of text, mentions may be grouped such that two mentions belong to the same group (“cluster”) if they refer to the same entity. It may be recognized that an entity is coreferent with and refers to the same entity or that information associated with the entity is referring to multiple distinct real-world individuals. Because the number of mentions and entities present within text of a document or across multiple documents can reach into the thousands or more, conventional approaches to entity resolution can be computationally demanding and thereby time consuming, particularly at large scale. It is with respect to these and other considerations that the various embodiments described below are presented.